title: Phylogenetic analysis of multiprobe fluorescence in situ hybridization data from tumor cell populations.
abstract: BACKGROUND
  Development and progression of solid tumors can be attributed to a process of mutations, which typically includes changes in the number of copies of genes or genomic regions. Although comparisons of cells within single tumors show extensive heterogeneity, recurring features of their evolutionary process may be discerned by comparing multiple regions or cells of a tumor. A useful source of data for studying likely progression of individual tumors is fluorescence in situ hybridization (FISH), which allows one to count copy numbers of several genes in hundreds of single cells. Novel algorithms for interpreting such data phylogenetically are needed, however, to reconstruct likely evolutionary trajectories from states of single cells and facilitate analysis of tumor evolution.
  
  
  RESULTS
  In this article, we develop phylogenetic methods to infer likely models of tumor progression using FISH copy number data and apply them to a study of FISH data from two cancer types. Statistical analyses of topological characteristics of the tree-based model provide insights into likely tumor progression pathways consistent with the prior literature. Furthermore, tree statistics from the resulting phylogenies can be used as features for prediction methods. This results in improved accuracy, relative to unstructured gene copy number data, at predicting tumor state and future metastasis.
  
  
  BACKGROUND
  Source code for software that does FISH tree building (FISHtrees) and the data on cervical and breast cancer examined here are available at ftp://ftp.ncbi.nlm.nih.gov/pub/FISHtrees.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Joint Carnegie Mellon/University of Pittsburgh Ph.D. Program in Computational Biology, Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA. sachowdh@andrew.cmu.edu
authors.forename: Salim Akhter
authors.initials: SA
authors.lastname: Chowdhury
authors.forename: Stanley E
authors.initials: SE
authors.lastname: Shackney
authors.forename: Kerstin
authors.initials: K
authors.lastname: Heselmeyer-Haddad
authors.forename: Thomas
authors.initials: T
authors.lastname: Ried
authors.forename: Alejandro A
authors.initials: AA
authors.lastname: Schäffer
authors.forename: Russell
authors.initials: R
authors.lastname: Schwartz
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000145:classification / Q000235:genetics* / Q000473:pathology; D018450:Disease Progression; D005260:Female; D018628:Gene Dosage; D006801:Humans; D017404:In Situ Hybridization, Fluorescence / Q000379:methods*; D010802:Phylogeny; D012984:Software; D002583:Uterine Cervical Neoplasms / Q000145:classification / Q000235:genetics* / Q000473:pathology